The Internet of Things (also referred to as the Cloud of Things) refers to an ad hoc network of uniquely identifiable embedded computing devices within the existing Internet infrastructure. In addition to or in conjunction with IoT, collaborative intelligence portends advanced connectivity of devices, systems, and robotic vehicles. The scope of things contemplated by collaborative intelligence and the IoT is unlimited, and may include devices such as heart monitoring implants, biochip transponders, automobile sensors, aerospace and defense field operation devices, unmanned ground vehicle (UGVs), unmanned aerial vehicles (UAVs), and public safety applications that assist fire-fighters in search and rescue operations, for example. Current market examples include home based networks that involve smart thermostats, light bulbs, and washer/dryers that utilize wifi for remote monitoring. Due to the ubiquitous nature of connected objects in the IoT, it is estimated that more than 30 billion devices will be wirelessly connected to the Internet of Things by 2020. Harnessing the processing capacity of the controllers and processors associated with these devices is one of the objectives of the present invention.
Computer processors traditionally execute machine coded instructions serially. To run a plurality of applications concurrently, a single processor interleaves instructions from various programs and executes them serially, although from the user's perspective the applications appear to be processed in parallel. True parallel or multi-core processing, on the other hand, is a computational approach that breaks large computational tasks into individual blocks of computations and distributes them among two or more processors. A computing architecture that uses task parallelism (parallel processing) divides a large computational requirement into discrete modules of executable code. The modules are then executed concurrently or sequentially, based on their respective priorities.
A typical multiprocessor system includes a central processing unit (“CPU”) and one or more co-processors. The CPU partitions the computational requirements into tasks and distributes the tasks to co-processors. Completed threads are reported to the CPU, which continues to distribute additional threads to the co-processors as needed. Presently known multiprocessing approaches are disadvantageous in that a significant amount of CPU bandwidth is consumed by task distribution; waiting for tasks to be completed before distributing new tasks (often with dependencies on previous tasks); responding to interrupts from co-processors when a task is completed; and responding to other messages from co-processors. In addition, co-processors often remain idle while waiting for a new task from the CPU.
A multiprocessor architecture in thus needed which reduces CPU management overhead, and which also more effectively harnesses and exploits available co-processing resources.